10
Temporal
…
Spatial
Dynamical Mechanistic Statistical
Statistical
Downscaling
Delta Change Weather
Classification Regression …
Geostatistical
Interpolation
Inverse
Distance
Weighting
(Thin-Plate)
Splines
Trend
Surfaces Kriging …
Hybrid Machine
Learning …
Downscaling Methodology Overview
Relate coarse-scale climate data to fine-scale climate data.
Purpose:
Generate fine-scale local climate projections from coarse-resolution global
climate model (GCM) or regional climate model (RCM) outputs.
Methodology:
Establish statistical relationships between large-scale predictors and local
climate observations.
Relate coarse-scale data to location in space and fine-scale covariates.
Purpose:
Estimate values at unsampled locations based on known observations,
creating continuous spatial datasets.
Methodology:
Utilize spatial statistical techniques that leverage spatial autocorrelation of
observed data points.